Using AI for Recruiting and Hiring – What Are the Risks and Rewards?

JUNE 6, 2023

Eighty-eight percent of companies globally use artificial intelligence (AI) in some way for HR, according to the Society for Human Resource Management (SHRM). When it comes to hiring specifically, data from the HR provider Predictive Hire shows that nearly 55% of companies are investing in AI that will enhance efficiency and enable data-driven judgments.

Benefits of AI

Companies use AI to help streamline the recruitment process, save time and resources, and make more informed hiring decisions. Some ways that AI is used in hiring include:

• Resume screening: AI can analyze resumes to identify relevant information, such as work experience, education, and skills. This can help recruiters identify the most qualified candidates more efficiently.
• Candidate matching: AI can match candidates to job descriptions based on their skills, qualifications, and experience.
• Pre-employment assessments: AI can evaluate candidates' cognitive abilities, skills, and personality traits.
• Video interviewing: AI can analyze candidates' facial expressions, tone of voice, and body language to help recruiters assess their suitability for a role.
• Diversity and inclusion: AI can help identify unconscious biases in the recruitment process, such as gender, age, or race. This can help companies create a more diverse and inclusive workforce.

Know the Risks

While using AI in the hiring process can be beneficial, it also raises some potential allegations and liabilities for employers, including:

1. Discrimination: AI systems can inadvertently perpetuate and even amplify biases in the recruitment process. For example, if the AI system is trained on biased data, it can lead to discriminatory outcomes, such as excluding qualified candidates from certain demographic groups. This can result in allegations of discrimination based on gender, race, and disability — as well as legal liabilities for the organization.
2. Privacy violations: AI may collect sensitive personal data about candidates, such as biometric data, without their consent or knowledge. This could violate privacy laws and result in legal liabilities for the company.
3. Inaccuracy: AI is not perfect and can make mistakes, which can impact hiring decisions.
4. Lack of human interaction: People can build relationships and trust with candidates. However, relying on AI can result in a negative candidate experience and hurt the company's ability to attract top talent.

Best Practices

Employers should adopt the following best practices when using AI in the recruitment process:

1. Understand the limitations and potential biases of AI: Be aware of the potential biases in AI systems, such as those based on historical data or training data that do not reflect the diversity of the workforce. Employers should also understand the limitations of AI and should not rely solely on this technology to make hiring decisions.
2. Use AI to augment, not replace, human judgment: Ensure that human oversight is present in the recruitment process to make final decisions.
3. Be transparent about the use of AI: Communicate clearly with candidates and employees about the use of AI in the hiring process, including what data is being collected, how it is being analyzed, and what decisions are being made based on the data.
4. Test the AI system for accuracy and bias: Test their AI system and make adjustments as necessary to ensure that it is fair, accurate, and unbiased.
5. Protect candidate privacy: Ensure that candidate data is protected and that they have obtained appropriate consent for the use of AI in the recruitment process. Employers should also ensure that candidate data is not used for any purposes other than recruitment.
6. Consider diversity and inclusion: Actively work to ensure that their AI systems do not perpetuate existing biases or create new ones, and strive to create a diverse and inclusive workforce.

Confirming that your AI system is set up properly and acts as a supplement to the process, rather than a replacement, will ensure that your search for quality candidates is done more efficiently and fairly.

Insurance Implications

Multiple coverages may come into play for this exposure — notably employment practices liability (EPL) and cyber insurance. Depending on your risk profile, you should also consider professional liability, including errors and omissions (E&O) and directors & officers (D&O).

1. EPL: Employers can face claims if their AI systems are alleged to result in discrimination against certain protected classes of candidates. Employers should ensure that their AI systems are designed and used in a manner that is non-discriminatory and compliant with applicable employment laws.
2. Cybersecurity: AI systems used in hiring can collect sensitive personal information about candidates, such as social security numbers and biometric data. This information can be a target for cybercriminals, resulting in data breaches, identity theft, and financial losses. Employers should ensure that their cybersecurity policies and procedures are up to date to protect against such risks.
3. Professional liability: Employers can face professional liability claims if their AI systems make errors or mistakes in the hiring process, such as incorrectly screening out qualified candidates, leaving less qualified candidates to provide services to customers and clients.
4. D&O: If a material adverse event impacts an organization’s valuation, the board of directors and senior management can find themselves in the crosshairs of shareholders or investors, creditors, employees, clients, and regulators. Litigation and investigations can be expensive to defend, and D&O accountability continues to be a focus of the plaintiffs’ bar.

Employers should also consult employment counsel to ensure that their AI systems comply with applicable laws and regulations and do not result in unintended consequences. USI clients should discuss insurance implications with their account service teams and review current and future EPL, cyber, professional liability and D&O liability policies.